In continual learning, plasticity refers to the ability of an agent to quickly adapt to new information. Neural networks are known to lose plasticity when processing non-stationary data streams. In this paper, we prop...
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The deployment of fifth-generation (5G) networks across various industry verticals is poised to transform communication and data exchange, promising unparalleled speed and capacity. However, the security concerns rela...
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Providing Quality of Service (QoS) under a variety of network conditions and security threats has become more difficult as the demand for large-scale wireless networks based on blockchain technology has increased. We ...
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ISBN:
(纸本)9798350381931
Providing Quality of Service (QoS) under a variety of network conditions and security threats has become more difficult as the demand for large-scale wireless networks based on blockchain technology has increased. We address these issues and significantly raise the overall QoS of blockchain-based networks in this paper by presenting an effective incremental learning bioinspired model This work is necessary because large-scale wireless networks must significantly improve their energy efficiency, throughput, delay reduction, and packet delivery ratio. Existing models frequently have difficulty meeting these demands and reducing the effects of different attacks, including Finney, Distributed Denial of Service (DDoS), Man-in-the-Middle (MITM), Sybil, and Masquerading scenarios. We suggest a novel strategy that combines two optimization techniques to get around these restrictions. In order to create sidechains, we first use Grey Wolf Optimization (GWO), which improves network partitioning and scalability in blockchain-based networks. Our model efficiently distributes the computational load and boosts system performance by dynamically adjusting the sidechain formation. In order to choose the best miner nodes for data mining between network nodes, we integrate Q Learning in the second step. The Q Learning algorithm makes intelligent decisions about the best miner nodes by taking into consideration parameters like throughput, latency, and energy efficiency. This deft choice of miner nodes improves network performance and QoS overall while optimizing data mining process. Through a thorough examination of spatial and temporal parameters, consensus is attained, allowing the system to assess the accuracy and dependability of mined blocks. This guarantees the blockchain network's integrity and security. Results from experiments show how effective our suggested model is. Our model improves energy efficiency by 8.5 percent, delays are cut by 10.4 percent, throughput is increased b
Hydrogen peroxide(H_(2)O_(2))photoproduction in seawater with metal-free photocatalysts derived from biomass materials is a green,sustainable,and ultra environmentally friendly ***,most photocatalysts are always corro...
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Hydrogen peroxide(H_(2)O_(2))photoproduction in seawater with metal-free photocatalysts derived from biomass materials is a green,sustainable,and ultra environmentally friendly ***,most photocatalysts are always corroded or poisoned in seawater,resulting in a significantly reduced catalytic ***,we report the metal-free photocatalysts(RUT-1 to RUT-5)with in-situ generated carbon dots(CDs)from biomass materials(Rutin)by a simple microwave-assisted pyrolysis *** visible light(λ≥420 nm,81.6 mW/cm^(2)),the optimized catalyst of RUT-4 is stable and can achieve a high H_(2)O_(2)yield of 330.36μmol/L in seawater,1.78 times higher than that in normal *** transient potential scanning(TPS)tests are developed and operated to in-situ study the H_(2)O_(2)photoproduction of RUT-4 under operation ***-4 has strong oxygen(O_(2))absorption capacity,and the O_(2)reduction rate in seawater is higher than that in *** cations in seawater further promote the photo-charge separation and facilitate the photo-reduction *** RUT-4,the conduction band level under operating conditions only satisfies the requirement of O_(2)reduction but not for hydrogen(H2)*** work provides new insights for the in-situ study of photocatalyst under operation condition,and gives a green and sustainable path for the H_(2)O_(2)photoproduction with metal-free catalysts in seawater.
Recognizing emotion from text is fundamental to machine learning and influences our understanding of human interaction. While English sentiment analysis has been well-researched, Bengali (Bangla) is still under-resear...
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The effect of winding chording on five-phase synchronous reluctance motor (SRM) modelled in phase variables is presented. The stator winding configuration is shifted a pole pitch from a full-pitch configuration to a 5...
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The cybersecurity of the power grid has gained increasing attraction in today's smart grid system. The dynamic load-altering attack (DLAA), which causes under-frequency trips by injecting an attacking load, and th...
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In this paper, we provide an extensive evaluation of machine learning (ML) and deep learning (DL) methods for automatic sleep stage classification using a single-channel electrocardiogram (ECG) signal. To explore ML m...
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In the general max–min fair allocation problem, there are m players and n indivisible resources, each player has his/her own utilities for the resources, and the goal is to find an assignment that maximizes the minim...
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— The direct pulsewidth modulation (PWM) ac–ac converters are seeing rapid development due to their single-stage power conversion with reduced footprints, due to the elimination of intermediate dc-link capacitor. Ho...
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